Wireless communications growth is characterized both by the increasing number of wireless devices such as smartphones, and their diversity (in both access method and applications). Computation is also evolving, towards a model based on networked access to distributed data and services. Today's wireless access is driven by user demand for convenient and continuous mobile access to services such as search, online social networks, location-based services, etc.
New usage and demands for higher application bandwidths is outrunning the growth in capacity of the wireless infrastructure. Some studies of these growth rates project significantly exceeding a capacity limit by 2016 with potential negative consequences that include dropped calls, congestion, slow download speeds, as well as increased deployment and operating costs.
Various approaches to these capacity problems exist. Signal-processing approaches that can better exploit available capacity continue to be developed, but large gains in performance (bits/Hz/meter2) are hard to obtain. Capacity improvements are technically easier to obtain through spatial diversity, but deploying ubiquitous access points that cover smaller areas is inherently expensive, and results in a profusion of specialized access points, each with a single purpose (e.g., for LTE, WiMax, GSM, or Wi-Fi). Deploying a large number of access points has been difficult, evident from the slow rate of femtocell adoption. Once deployed, access points remain in service for long periods of time and rarely evolve, inhibiting deployment of new protocols.
A second and often-neglected issue in deployment is the local wireless environment. Today, cellular carriers traverse neighborhoods measuring coverage to locate and fill holes as necessary, but this costly and manpower-intensive process is difficult to replicate for home-deployed femtocells. Even knowledgeable home users may have difficulty locating (and obtaining good throughput from) their Wi-Fi routers due, for example, to interference.